Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Protein-protein Interfaces02:04

Protein-protein Interfaces

14.7K
Many proteins form complexes to carry out their functions, making protein-protein interactions (PPIs) essential for an organism's survival. Most PPIs are stabilized by numerous weak noncovalent chemical forces. The physical shape of the interfaces determines the way two proteins interact. Many globular proteins have closely-matching shapes on their surfaces, which form a large number of weak bonds. Additionally, many PPIs occur between two helices or between a surface cleft and a...
14.7K
Protein-Protein Interfaces02:04

Protein-Protein Interfaces

4.5K
4.5K
Cable Subjected to Its Own Weight01:13

Cable Subjected to Its Own Weight

795
Overhead power transmission lines rely on cables to carry electricity across large distances. To ensure the stability and functionality of these lines, it is crucial to understand the shape and tension experienced by the cables under the influence of their weight.
A generalized loading function is employed to analyze a cable subjected to its own weight. This function considers the force acting along the cable's arc length rather than its projected length, providing a more accurate...
795
Cable Subjected to Concentrated Loads01:28

Cable Subjected to Concentrated Loads

1.4K
Flexible cables are commonly used in various applications for support and load transmission. Consider a cable fixed at two points and subjected to multiple vertically concentrated loads. Determine the shape of the cable and the tension in each portion of the cable, given the horizontal distances between the loads and supports.
1.4K
Cable Subjected to a Distributed Load01:24

Cable Subjected to a Distributed Load

1.1K
The analysis of suspension bridges is a complex and critical process that involves multiple factors, including the shape and tension of the main cables. The main cables of suspension bridges are subjected to distributed loads, which result in changes in tensile forces and deformation of the cable. These loads must be carefully considered to ensure that the bridge is safe and capable of supporting the weight of different loads.
1.1K
Assessment of the Gastrointestinal System I: Subjective Data01:17

Assessment of the Gastrointestinal System I: Subjective Data

660
Assessing the gastrointestinal (GI) system is a complex process that begins with collecting subjective data. This data, collected through patient interviews, provides crucial insights into the patient's health history, perception patterns, and lifestyle habits, all contributing significantly to GI health.
Health History
The initial step in assessing the GI system is obtaining a comprehensive health history. This includes inquiring about the patient's history or presence of problems...
660

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Applications of electromyography in Amyotrophic Lateral Sclerosis: A systematic review.

PloS one·2026
Same author

Quantifying Inter- and Intra-Subject Variability of Sensorimotor Desynchronization Induced by Median Nerve Stimulation and Motor Imagery for BCI.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

Reliable predictor of BCI motor imagery performance using median nerve stimulation.

Journal of neural engineering·2025
Same author

Attentional Inhibition Ability Predicts Neural Representation During Challenging Auditory Streaming.

Cognitive, affective & behavioral neuroscience·2025
Same author

Large scale investigation of the effect of gender on mu rhythm suppression in motor imagery brain-computer interfaces.

Brain computer interfaces (Abingdon, England)·2024
Same author

Electromyography as a tool to motion analysis for people with Amyotrophic Lateral Sclerosis: A protocol for a systematic review.

PloS one·2024
Same journal

Vowel acoustic parameters in speech assessment and rehabilitation of minimally verbal and speech-motor-impaired autistic children: a narrative review.

Frontiers in human neuroscience·2026
Same journal

Toward clinical translation of TMS-EEG: an integrative review of multidimensional neurophysiological measures.

Frontiers in human neuroscience·2026
Same journal

The causal efficacy of consciousness: a neuroscientific analysis and explanation.

Frontiers in human neuroscience·2026
Same journal

Temporal-oscillatory entrainment: a multi-timescale framework for rhythmic coordination from neural to social frequencies.

Frontiers in human neuroscience·2026
Same journal

Role of AQP4 in ameliorating heat stress-induced cellular injury in a cell line model through active heat acclimation.

Frontiers in human neuroscience·2026
Same journal

Correction: Cognitive state monitoring for neuroadaptive information visualization.

Frontiers in human neuroscience·2026
See all related articles

Related Experiment Video

Updated: Jan 29, 2026

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
06:09

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation

Published on: September 8, 2023

948

Can a Subjective Questionnaire Be Used as Brain-Computer Interface Performance Predictor?

Sébastien Rimbert1, Nathalie Gayraud2, Laurent Bougrain1

  • 1Université de Lorraine, Inria, LORIA, Neurosys Team, Nancy, France.

Frontiers in Human Neuroscience
|February 8, 2019
PubMed
Summary
This summary is machine-generated.

The Motor Imagery Questionnaire (MIQ-RS) cannot predict Brain Computer Interface (BCI) performance. Instead, BCI success is linked to a user's manual activity habits and practice frequency.

Keywords:
BCI-illiteratebrain-computer interfacekinesthetic motor imagerymotor imagery questionnaireprediction of accuracy

More Related Videos

Performing Behavioral Tasks in Subjects with Intracranial Electrodes
12:10

Performing Behavioral Tasks in Subjects with Intracranial Electrodes

Published on: October 2, 2014

11.9K
An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
10:51

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

Published on: March 10, 2011

14.2K

Related Experiment Videos

Last Updated: Jan 29, 2026

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
06:09

P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation

Published on: September 8, 2023

948
Performing Behavioral Tasks in Subjects with Intracranial Electrodes
12:10

Performing Behavioral Tasks in Subjects with Intracranial Electrodes

Published on: October 2, 2014

11.9K
An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces
10:51

An Experimental Platform to Study the Closed-loop Performance of Brain-machine Interfaces

Published on: March 10, 2011

14.2K

Area of Science:

  • Neuroscience
  • Rehabilitation Engineering
  • Human-Computer Interaction

Background:

  • Predicting Brain Computer Interface (BCI) performance is crucial for user adaptation and research.
  • Subjective questionnaires like the Motor Imagery Questionnaire Revised-Second Edition (MIQ-RS) have been explored as potential predictors.
  • Further validation is needed to confirm their effectiveness in estimating BCI capabilities.

Purpose of the Study:

  • To determine if the MIQ-RS can estimate performance in Motor Imagery (MI)-based BCIs.
  • To identify alternative markers for predicting BCI performance if the MIQ-RS proves ineffective.

Main Methods:

  • Recorded electroencephalogram (EEG) signals from 35 healthy volunteers using a BCI.
  • Administered the MIQ-RS questionnaire to participants prior to BCI use.
  • Performed offline analysis correlating MIQ-RS scores with the performance of four BCI classification methods.

Main Results:

  • No significant correlation was found between MIQ-RS scores and BCI performance.
  • BCI performance showed a correlation with participants' habits and frequency of practicing manual activities.

Conclusions:

  • The MIQ-RS is not a reliable tool for estimating MI-based BCI performance.
  • Habitual manual activity and practice frequency may serve as potential predictors for BCI success.